A Zoom-in Analysis of I/O Logs to Detect Root Causes of I/O Performance Bottlenecks

Conference · Tue Jan 01 00:00:00 EST 2019

DOI:https://doi.org/10.1109/CCGRID.2019.00021· OSTI ID:1562878

Wang, Teng; Byna, Suren; Lockwood, Glenn K.; Snyder, Shane; Carns, Philip; Kim, Sunggon; Wright, Nicholas J.

Scientific applications frequently spend a large fraction of their execution time in reading and writing data on parallel file systems. Identifying these I/O performance bottlenecks and attributing root causes are critical steps toward devising optimization strategies. Several existing studies analyze I/O logs of a set of benchmarks or applications that were run with controlled behaviors. However, there is still a lack of general approach that systematically identifies I/O performance bottlenecks for applications running "in the wild" on production systems. In this study, we have developed an analysis approach of "zooming in" from platform-wide to application-wide to job-level I/O logs for identifying I/O bottlenecks in arbitrary scientific applications. We analyze the logs collected on a Cray XC40 system in production over a two-month period. This study results in several insights for application developers to use in optimizing I/O behavior.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Science - Office of Advanced Scientific Computing Research
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1562878
• Resource Relation: Conference: 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 05/14/19 - 05/17/19, Larnaca, CY
• Country of Publication: United States
• Language: English